The present invention relates to suppression of noise in signal waveforms.
Monitoring systems, such as personal health monitors, acquire and extract data from signal waveforms. Unfortunately, signal waveforms often exhibit unwanted noise bursts or spikes caused by transient input stimulus. For example, when a microphone of a personal health monitor is mounted on the human body, the microphone may detect abrupt hits, clothing scrapes and other impulse sounds that manifest themselves as noise bursts in a raw acoustic signal waveform. When an acoustic signal energy waveform is computed from the raw waveform, the noise bursts present as noise spikes in the energy waveform which, if not suppressed, can prevent or hinder extraction of reliable data, such as respiration or heart rate data, from the energy waveform.
Many conventional techniques for suppressing noise events in signal waveforms have relied mainly on low-pass frequency or median filtering. These conventional techniques have shortcomings in terms of inadequately suppressing noise events, dramatically degrading signal quality, or both. FIG. 1 shows an exemplary energy waveform exhibiting noise spikes that are inadequately suppressed by conventional filtering. The unfiltered waveform 110 exhibits large amplitude noise spikes. After application of a low-pass filter to waveform 110, the noise spikes are somewhat suppressed, but the low-pass filtered waveform 120 still has noise spikes of moderate amplitude. These noise spikes could perhaps be further reduced by applying a low-pass filter covering a narrower band, but applying a narrower band low-pass filter would remove a substantial portion of the signal of interest, reducing its amplitude and distorting its shape. Similarly, application of a median filter to unfiltered waveform 110 results in a median filtered waveform 130 that continues to have moderate amplitude noise spikes. These noise spikes could perhaps be further reduced by applying a median filter of larger sample size, but applying a larger sample size median filter would further degrade the quality of the signal of interest by reducing signal resolution. Moreover, applying a median filter, regardless of sample size, raises the noise floor in the signal since the samples that exhibit large noise are part of the sample group used to identify the median samples.